We invest in foundational AI research that pushes the boundaries of what intelligent systems can do — and everything we learn feeds directly into what we build for clients.
We focus on making AI models more efficient, more accurate, and easier to deploy at scale. Our research helps us build systems that run faster, cost less, and perform better for our clients.
Making AI systems respond faster while using fewer resources
Smaller, more capable models that can run anywhere
Designed to work on real hardware in real environments
Building intelligent agents capable of multi-step reasoning, tool use, and autonomous task completion. Our agents combine planning, memory, and execution capabilities.
Complex task decomposition and execution
API calls, code execution, and retrieval
Long-term context retention and recall
Our research spans multiple domains within AI, each contributing to more capable and reliable systems.
Teaching AI systems to think step-by-step and produce verifiable, trustworthy outputs.
AI that understands, writes, and improves software — from bug detection to automated testing.
Rigorous methods to measure, benchmark, and guarantee the performance of AI systems.
We're open to research collaborations with academic institutions, industry partners, and government organizations.